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Record W2804909943 · doi:10.3168/jds.2018-14592

Evaluation by employees of employee management on large US dairy farms

2018· article· en· W2804909943 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of Calgary
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsBusinessMilkingEmployee retentionMarketingLikert scalePhoneEmployee engagementWork (physics)TeamworkJob satisfactionPerceptionPsychologyPublic relationsManagementEngineering

Abstract

fetched live from OpenAlex

Employees, many of whom are not native English speakers, perform the majority of work on large US dairy farms. Although management of employees is a critical role of dairy owners and managers, factors that improve employee engagement and retention are not well known. Objectives were to (1) identify key dairy farm employee management issues based on employee perceptions, (2) evaluate strengths and weaknesses of farms based on employee responses, (3) investigate differences between Latino and English-speaking employees, and (4) investigate differences in perception between employers and employees. Employees from 12 US dairy farms (each with a minimum of 10 employees) were interviewed by phone following a questionnaire provided. Employees provided their responses to 21 Likert scale questions and 8 open-ended questions. There was a wide range in employee turnover among farms (<10 to >100%). Latino employees had much shorter tenure and were more often employed in milking and livestock care than English-speaking employees. Employee perceptions differed among farms regarding whether they would recommend their farm as a place to work, teamwork within the dairy, whether rules were fairly applied, availability of tools and equipment, clear lines of supervision, and recognition for good work in the previous 15 d. Latino employees (n = 91) were more positive in many of these measures than their English-speaking counterparts (n = 77) but less often provided ideas to their employer on how to improve the business. Employers, surveyed on how they thought their employees would answer, underestimated employee responses on several questions, particularly the interest of employees in learning about dairy. When asked to cite 3 goals of the operation, there were differences among owners, managers, and employees. Although employees rated their commitment to the farm and their interest in learning as high, based on turnover, there was an obvious disparity between reality and ideal employee management. Consequently, employers should act on identified management shortfalls to improve employee retention.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.272
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it